Instructions to use ProbeX/Model-J__SupViT__model_idx_0870 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProbeX/Model-J__SupViT__model_idx_0870 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProbeX/Model-J__SupViT__model_idx_0870") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0870") model = AutoModelForImageClassification.from_pretrained("ProbeX/Model-J__SupViT__model_idx_0870") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 462b7d986379398101c049632b6d97e1eda9139615146b9e92ead1f864a592a5
- Size of remote file:
- 5.37 kB
- SHA256:
- b17b9a3625a1cae91c94488efb9310e52d71df00269768c5998a94bc4964a3c2
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